The public assistance system is supposed to offer a bridge between poverty and self-sufficiency. Families receive benefits such as Temporary Assistance for Needy Families (TANF) or Supplemental Nutrition Assistance Program (SNAP) to soften the impact of loss of income. The programs are intended to be limited in duration and provide a very modest amount of financial support. Some families are fortunate to also receive a housing voucher or a child care subsidy to help offset basic expenses. Eligibility for benefits varies by program and is based on different criteria, most of which are linked to personal income. This study asks: what happens when benefits are cut before individuals reach economic stability? This is frequently called the “benefits cliff.”

Until relatively recently, developing hybrid simulation models using more than one simulation paradigm was a challenging task which required a degree of ingenuity on behalf of the modeler. Generally speaking, such hybrid models either had to be coded from scratch in a programming language, or developed using two (or more) different off-the-shelf software tools which had to communicate with each other through a user-written interface. Nowadays a number of simulation tools are available which aim to make this task easier. This paper does not set out to be a formal review of such software, but it discusses the increasing popularity of hybrid simulation and the rapidly developing market in hybrid modeling tools, focusing specifically on applications in health and social care and using experience from the Care Life Cycle project and elsewhere.

Disaster, whether manmade or natural, can have a catastrophic impact on a populated area. Sometimes, the disaster is so devastating that it requires a large-scale evacuation. As a result, evacuation plans have become a necessity. One such evacuation plan is the regional hub reception center (RHRC), which will help evacuate the careless population when an evacuation is needed. Using AnyLogic as a simulation modeling software, an RHRC model was developed to test the efficiency of the proposed plan.

Developing countries are faced with finding novel and humane ways to permanently reduce and control their dog population. Agent-based models developed to describe dog populations represent a unique, platform for using computer based simulation to identify control strategies with the greatest potential for success, aid in the design of more effective control measures, and provide a means to evaluate the success of different interventions.

The objective of this paper is to propose and test a framework for integrated assessment of infrastructure systems at the interface between the dynamic behaviors of assets, agencies, and users. For the purpose of this study a hybrid agent-based/mathematical simulation model is created and tested using a numerical example related to a roadway network.

Modelling real workforce choices accurately via Agent Based Models and System Dynamics requires
input data on the actual preferences of individual agents. Often lack of data means that analysts can have
an understanding of how agents move through the system, but not why, and when.

This paper discusses the development of a simulation model to mimic a return to work phenomenon of Social Security Disability Insurance (SSDI) enrollees in the United States. Agent Based and Bayesian Network methods are used within a multi-method simulation model to capture system conditions and enrollee behavior.

This paper describes a socio-technical study based on physical world scenarios of deceptive behaviour occurring in a virtual collaborative environment. An agent-based modelling (ABM) approach was adopted to visualise trustworthiness that can signal deceptive behaviour in virtual communications among social actors. The modelling strategies were guided by attribution theories toward an agent’s perceived trustworthiness.

One of the challenges in developing policy for dealing with asocial behavior, such as burglary, vehicle theft, or violent crimes is the seemingly unpredictable rise and fall of activity. In retrospect these cycles in crime are often attributed to changes in factors such the size of a police force, level unemployment, or high school drop-out rate. What causes changes in these factors can some times be external to a local community, such as economic shifts affecting tax revenue, however many are internally linked. For example when crime is high, there is a call for more police and when crime is low, there is a justification for reducing the size of the force. Therefore, understanding how these factors are linked together as a whole may allow for better policies that reduce asocial behavior further and create more stability in the long term.